Voltage regulation and control evaluation method based on polymorphic reactive power resource suitability

Abstract

The invention discloses a voltage regulation and control evaluation method based on polymorphic reactive power resource suitability, and belongs to the technical field of steady-state analysis of a power system, and the method comprises the steps: S1, carrying out the improvement of a simulation power system based on a voltage regulation and control scheme, and obtaining an optimized simulation system; s2, based on load flow calculation, obtaining an electrical parameter of the node in the first scene, and based on the electrical parameter, obtaining a first fitness score of the first reactive power resource; s3, based on the Jacobian matrix, obtaining a sensitivity value of the node in a second scene, and based on the sensitivity value, obtaining a second fitness score of a second reactive power resource; s4, obtaining the weight of the first fitness score and the weight of the second fitness score based on a comprehensive evaluation system constructed by an entropy weight method; and S5, evaluating the voltage regulation and control scheme according to the obtained fitness score and weight. The problem of low reliability of a scheme evaluation result caused by lack of accurate quantification of fitness of various reactive resources in different scenes is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of steady-state analysis of power systems, and in particular to a voltage regulation and evaluation method based on the adaptability of multi-form reactive resources. Background Art

[0002] With the high proportion of photovoltaic access to the distribution network, its intermittent and random output, superimposed with the volatility of multiple types of loads, easily causes the problem of feeder voltage over-limit. Since reactive power is not suitable for long-distance large-scale transmission and the voltage regulation is localized, there is a lack of reasonable solutions for voltage regulation. For example, the patent number CN116865284A is a voltage regulation scheme adaptability evaluation method that considers voltage regulation effect and cost, including traversing the entire distribution network, counting all types of controllable reactive resources and their typical daily output characteristics in four seasons; constructing an optimal reactive scheduling model to obtain the typical daily scheduling plan for each controllable resource; proposing a method for calculating the distribution network voltage over-limit degree score under the scheduling plan; proposing a method for calculating the distribution network voltage over-limit probability score under the scheduling plan; proposing a method for calculating the distribution network voltage regulation plan cost score; based on the hierarchical analysis method, the voltage over-limit degree score, the voltage over-limit probability score, and the voltage regulation plan cost score are weighted to construct a distribution network voltage regulation plan adaptability evaluation system. The above scheme takes into account multiple factors such as voltage regulation effect and voltage regulation cost, and improves the comprehensiveness and practicality of the voltage regulation plan adaptability evaluation results. However, in the above scheme, the proposed voltage over-limit degree score and voltage over-limit probability score calculation method, although it can evaluate the impact of the scheduling scheme on voltage stability, does not fully consider the differences in different reactive resources in improving voltage stability, and the weighting only through the hierarchical analysis method is too subjective. Therefore, there is a lack of accurate quantification of the adaptability of various reactive resources in different scenarios, which will lead to low reliability of the evaluation results. Summary of the invention

[0003] In view of the problem that the existing technology lacks accurate quantification of the adaptability of various reactive resources in different scenarios, resulting in low reliability of scheme evaluation results. The present invention provides a voltage control evaluation method based on the adaptability of multi-form reactive resources, which accurately obtains the fitness scores of corresponding reactive resources in corresponding scenarios through the steady-state analysis capability of power flow calculation and the sensitivity analysis characteristics of Jacobian matrix, fully considering the differentiation of different reactive resources in improving voltage stability, and obtains the weights of fitness scores of various reactive resources from multiple subjective and objective aspects through hierarchical analysis method and entropy weight method. Further, the fitness scores of reactive resources are combined with the weights of the fitness scores of corresponding reactive resources to evaluate the scheme, solving the problem that the reliability of scheme evaluation results is low due to the lack of accurate quantification of the adaptability of various reactive resources in different scenarios. The comprehensiveness and reliability of scheme evaluation are significantly improved.

[0004] In order to solve the above technical problems, the present invention provides a voltage regulation and evaluation method based on the adaptability of multi-form reactive resources, comprising the following steps: S1: Based on the operating characteristics of multi-form reactive resources and the reactive resource demand of the distribution network in different scenarios, the voltage control scheme is obtained, and the simulated power system is improved based on the voltage control scheme to obtain an optimized simulation system; S2: Based on power flow calculation, obtain the electrical parameters of the nodes in the optimization simulation system in the first scenario in different scenarios, and obtain the first fitness score of the first reactive resource in the multi-form reactive resources based on the electrical parameters; S3: Based on the Jacobian matrix, using the electrical signal of the input optimization simulation system to obtain a sensitivity value of the node in a second scenario in different scenarios, and obtaining a second fitness score of a second reactive resource in the multi-modal reactive resource based on the sensitivity value; S4: construct a comprehensive evaluation system based on the analytic hierarchy process and the entropy weight method, and obtain the weight of the first fitness score and the weight of the second fitness score based on the comprehensive evaluation system; S5: Evaluate the voltage control scheme based on the first fitness score, the weight of the first fitness score, the second fitness score, and the weight of the second fitness score.

[0005] After adopting the above technical solution, the present invention has the following advantages: Taking into account the differences in improving voltage stability of different reactive resources, the steady-state analysis capability of power flow calculation and the sensitivity analysis characteristics of the Jacobian matrix, the fitness scores of corresponding reactive resources in corresponding scenarios can be accurately obtained through power flow calculation and Jacobian matrix respectively. Taking into account the differences in subjective evaluation and the objectivity of the entropy weight method, a comprehensive evaluation system is constructed to accurately obtain the weights of the fitness scores of various reactive resources from multiple subjective and objective aspects. Furthermore, the fitness scores of reactive resources are combined with the weights of the fitness scores of corresponding reactive resources to evaluate the scheme, which significantly improves the comprehensiveness and reliability of the scheme evaluation and solves the problem of low reliability of scheme evaluation results due to the lack of accurate quantification of the fitness of various reactive resources in different scenarios.

[0006] Preferably, in S2, the expression for obtaining the electrical parameters of the nodes in the optimization simulation system in the first scenario in different scenarios based on the power flow calculation is: In the formula, represents the active power injected by node i in the nodes under the first scenario, represents the reactive power injected by node i in the first scenario, U i is the voltage phase difference at node i, U j is the voltage amplitude of node j in the node, θij is the voltage phase difference between node i and node j, G ij and B ij are the conductance and susceptance between node i and node j in the admittance matrix, Ω N is the set of all nodes except the PQ node, Ω pQ is the set of PQ nodes in the node, N bus Indicates the total number of nodes.

[0007] Due to the powerful steady-state analysis capability of power flow calculation, it is particularly suitable for analyzing the operating status under long time scales. The first scenario is a long time scale scenario, so the electrical parameters under the first scenario are obtained through power flow calculation, which improves the accuracy of the electrical parameters under the first scenario.

[0008] Preferably, in S2, obtaining a first fitness score of a first reactive resource in the multi-form reactive resources based on the electrical parameter includes: Obtaining a fitness score of the node in the supporting scenario based on the electrical parameters of the node in the supporting scenario in the first scenario and the reference electrical parameters; Obtaining fitness scores of nodes in the stabilization scenario based on electrical parameters of nodes in the simulated power system in the stabilization scenario in the first scenario and electrical parameters of nodes in the optimized simulation system in the stabilization scenario in the first scenario; The fitness score of the node in the supporting scenario and the fitness score of the node in the stabilizing scenario are the first fitness score of the first reactive resource.

[0009] Preferably, in S3, the step of obtaining the sensitivity value of the node in the second scenario in different scenarios by using the electrical signal of the input optimization simulation system based on the Jacobian matrix includes: Based on the Jacobian matrix, the sensitivity matrix of the node in the second scenario is obtained by using the electrical signal of the input optimization simulation system; and the sensitivity value of the node in the second scenario is obtained based on the sensitivity matrix.

[0010] Due to the sensitivity analysis characteristics of the Jacobian matrix, it is particularly suitable for analyzing instantaneous operating conditions. The second application scenario is an instantaneous scenario, so the sensitivity value in the second scenario is obtained through the Jacobian matrix, which improves the accuracy of the sensitivity value in the second scenario.

[0011] Preferably, the expression for obtaining the sensitivity matrix of the node in the second scenario based on the Jacobian matrix and using the electrical signal of the input optimization simulation system is: Where ΔO and ΔQ are respectively the active power change matrix and reactive power change matrix injected by the node in the second scenario, Δθ and ΔU are respectively the voltage phase angle and amplitude change matrices of the node, J is the Jacobian matrix, J -1 is the sensitivity matrix of the node in the second scenario.

[0012] Preferably, S4 includes: S41: taking the first weight of the first fitness score and the first weight of the second fitness score as the parent indicator in the analytic hierarchy process in the comprehensive evaluation system, and defining the sub-indicators under the parent indicators in the analytic hierarchy process based on the evaluation requirements; S42: Compare the sub-indicators under the parent indicator in pairs, and then establish a judgment matrix, and obtain the first weight of the first fitness score and the first weight of the second fitness score based on the judgment matrix; S43: normalizing the sub-indicators based on the entropy weight method in the comprehensive evaluation system to obtain a normalized result, and obtaining a second weight of the first fitness score and a second weight of the second fitness score based on the normalized result; S44: Obtaining a weight of the first fitness score based on a first weight of the first fitness score and a second weight of the first fitness score, and obtaining a weight of the second fitness score based on the first weight of the second fitness score and the second weight of the second fitness score.

[0013] Taking into account the differences in subjective evaluation and the objectivity of the entropy weight method, a comprehensive evaluation system is constructed to accurately obtain the weights of the fitness scores of various reactive resources from multiple subjective and objective aspects. Furthermore, the combined weights of the fitness scores of reactive resources are obtained based on the weights obtained from multiple subjective and objective aspects, which avoids the one-sidedness of single weighting, improves the rationality of weight distribution, and further, to a certain extent, improves the reliability of the evaluation results.

[0014] Preferably, in S42, the judgment matrix A=(a ij ) n*n , where a ij It indicates the importance of the i-th sub-indicator under the parent indicator relative to the j-th sub-indicator, and n is the number of sub-indicators under the parent indicator.

[0015] Preferably, in S42, the obtaining of the first weight of the first fitness score and the first weight of the second fitness score based on the judgment matrix includes: The judgment matrix is ​​summed up by columns to obtain the total number of elements in each column, and the judgment matrix is ​​normalized based on the total number of columns to obtain the process matrix; The process matrix is ​​summed row by row to obtain a weight vector, and a first weight of the first fitness score and a first weight of the second fitness score are obtained based on the weight vector.

[0016] Preferably, in S43, the obtaining of the second weight of the first fitness score and the second weight of the second fitness score based on the normalization processing result includes: Based on the normalization result, the entropy value of the sub-indicator is calculated, the weight of the sub-indicator is obtained based on the entropy value, and the second weight of the first fitness score and the second weight of the second fitness score are obtained based on the weight of the sub-indicator.

[0017] Preferably, S5 includes: S51: obtaining a first product of the first fitness score and the weight of the first fitness score, and obtaining a second product of the second fitness score and the weight of the second fitness score; S52: Evaluate the voltage control scheme based on the sum of the first product and the second product. Evaluate the scheme by combining the fitness score of the reactive resource with the weight of the fitness score of the corresponding reactive resource, which significantly improves the comprehensiveness and reliability of the scheme evaluation.

[0018] Beneficial effects of this program: Taking into account the different demands for reactive resources in different load scenarios, in order to be able to more accurately adjust the voltage level of the distribution network in the future, a voltage control solution is obtained based on the operating characteristics of multi-form reactive resources and the reactive resource demands of the distribution network in different scenarios, which reduces energy waste and improves energy utilization. Taking into account the differences in improving voltage stability of different reactive resources, the steady-state analysis capability of power flow calculation and the sensitivity analysis characteristics of Jacobian matrix, the fitness scores of corresponding reactive resources in corresponding scenarios can be accurately obtained through power flow calculation and Jacobian matrix. Taking into account the differences in subjective evaluation and the objectivity of entropy weight method, a comprehensive evaluation system is constructed to accurately obtain the weights of fitness scores of various reactive resources from multiple subjective and objective aspects. Furthermore, the fitness scores of reactive resources are combined with the weights of the fitness scores of corresponding reactive resources to evaluate the scheme, which significantly improves the comprehensiveness and reliability of scheme evaluation. The problem of low reliability of scheme evaluation results due to the lack of accurate quantification of the adaptability of various reactive resources in different scenarios is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Other features, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention. Also, the same reference symbols are used throughout the drawings to represent the same parts.

[0020] Figure 1It is a flow chart of the voltage regulation and evaluation method based on the adaptability of multi-form reactive resources of the present invention; Figure 2 A network topology diagram of an IEEE 33 node system in an embodiment of the present invention; Figure 3 A comparison diagram of the voltage amplitudes of various nodes in a supporting scenario in an embodiment of the present invention; Figure 4 The figure is a comparison diagram of the voltage amplitudes of various nodes whether connected to the SVC in the leveling scenario in the embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0022] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) therein can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the drawings; the process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0023] Embodiment 1: like Figure 1 As shown, the voltage regulation evaluation method based on the adaptability of multi-form reactive resources includes the following steps: S1: Based on the operating characteristics of multi-form reactive resources and the reactive resource demand of the distribution network in different scenarios, a voltage control scheme is obtained, and the simulated power system is improved based on the voltage control scheme to obtain an optimized simulation system.

[0024] Multi-form reactive resources include load-controlled voltage-changing transformers, capacitors, static VAR compensators, and photovoltaic inverters. Different scenarios include support scenarios, leveling scenarios, and sag mitigation scenarios. The operating characteristics of reactive resources and the reactive resource requirements of the distribution network in the power system are statistically analyzed to obtain voltage control solutions. According to the voltage control solution, the above reactive resources are installed on the simulated power system, such as Figure 2As shown, in this embodiment, the IEEE33 node system is selected as the simulated power system, and reactive resources are installed according to the voltage control scheme. The voltage control scheme is specifically as follows: in the support scenario, with 1h as the time scale and 24h as the execution cycle, OLTC and capacitor groups are installed on the basis of the IEEE33 node system. The OLTC is located at the head end of the distribution network, and the secondary voltage adjustment range is 0.90~1.1 (pu), -8~+8, a total of 17 gears, and the step size is 0.125 (pu). At the same time, 8 groups and 12 groups of capacitors are connected at nodes 16 and 28 respectively, and the compensation capacity of a single group is 0.1Mvar; in the leveling scenario, with 15min as the time scale and 24 hours as the execution cycle, on the system of Scheme 1, SVC is installed at node 10, and the maximum installed capacity is selected as 50Mvar; in the sag relief scenario, photovoltaic inverters are provided at nodes 23 in the IEEE33 system. The voltage control scheme takes into account the different demands for reactive resources in different load scenarios. By matching the supply and demand of reactive resources, the flow of reactive power in the power grid is reduced, thereby reducing power grid losses. At the same time, the configuration and operation of reactive compensation equipment are optimized, avoiding over-compensation or under-compensation, thereby improving the utilization rate of reactive resources.

[0025] S2: Based on power flow calculation, obtain the electrical parameters of the nodes in the optimization simulation system in the first scenario in different scenarios, and obtain the first fitness score of the first reactive resource in the multi-form reactive resources based on the electrical parameters.

[0026] In S2, the expression for obtaining the electrical parameters of the nodes in the optimization simulation system in the first scenario in different scenarios based on the power flow calculation is: In the formula, represents the active power injected by node i in the nodes under the first scenario, represents the reactive power injected by node i in the first scenario, U i is the voltage phase difference at node i, U j is the voltage amplitude of node j in the node, θ ij is the voltage phase difference between node i and node j, G ij and B ij are the conductance and susceptance between node i and node j in the admittance matrix, Ω N is the set of all nodes except the PQ node, Ω pQ is the set of PQ nodes in the node, N bus Indicates the total number of nodes.

[0027] In S2, the obtaining of a first fitness score of a first reactive resource in the multi-form reactive resource based on electrical parameters comprises: obtaining a fitness score of a node in a supporting scenario based on electrical parameters of the node in a supporting scenario in the first scenario and reference electrical parameters; Obtaining fitness scores of nodes in the stabilization scenario based on electrical parameters of nodes in the simulated power system in the stabilization scenario in the first scenario and electrical parameters of nodes in the optimized simulation system in the stabilization scenario in the first scenario; The fitness score of the node in the supporting scenario and the fitness score of the node in the stabilizing scenario are the first fitness score of the first reactive resource.

[0028] In this embodiment, the electrical parameters that appear are all voltage amplitudes, the first reactive resources are OLTC, capacitors, and SVG, and the expression for obtaining the fitness score of the node in the supporting scenario based on the electrical parameters of the node in the supporting scenario and the reference electrical parameters is S=100*(1-|ΔU i |), where S is the fitness score of the node in the supporting scenario, ΔU i is the voltage change at node i, ΔU i =U i -U ref , where U i is the voltage amplitude of node i in the support scenario, U ref is the reference voltage amplitude. Based on the electrical parameters of the nodes in the simulated power system in the smoothing scenario and the electrical parameters of the nodes in the optimized simulated system in the smoothing scenario, the expression for the fitness score of the nodes in the smoothing scenario is obtained as follows: Where S is the fitness score of the node in the smoothing scenario, ΔU j is the voltage change at node j, ΔU b，j To optimize the voltage amplitude of the nodes in the simulation system under the smoothing scenario, ΔU j =ΔU a，j -ΔU b，j , where ΔU a，j To simulate the voltage amplitude of the nodes in the power system in the smoothing scenario. According to the above formula, the fitness scores of the nodes in the support scenario are (99.24, 96.65, 95.81, 95.56, 99.78), and the fitness scores of the nodes in the smoothing scenario are (59.5, 76.5, 80.4, 80.6, 69.8). Through the powerful steady-state analysis capability of the flow calculation, the accurate electrical parameters, namely the voltage amplitude, are obtained, and then the accurate voltage amplitude is input into the corresponding calculation formula, which can accurately obtain the fitness scores of the nodes in the support scenario and the smoothing scenario, respectively, and then facilitate the performance of the voltage control scheme in the support scenario and the smoothing scenario through the corresponding node fitness scores in different scenarios, which helps to improve the reliability and comprehensiveness of the scheme evaluation.

[0029] S3: Based on the Jacobian matrix, the electrical signal of the input optimization simulation system is used to obtain the sensitivity value of the node in the second scenario in different scenarios, and the second fitness score of the second reactive resource in the multi-modal reactive resource is obtained based on the sensitivity value.

[0030] In S3, the step of obtaining the sensitivity value of the node in the second scenario in different scenarios by using the electrical signal of the input optimization simulation system based on the Jacobian matrix includes: Based on the Jacobian matrix, the sensitivity matrix of the node in the second scenario is obtained by using the electrical signal of the input optimization simulation system; and the sensitivity value of the node in the second scenario is obtained based on the sensitivity matrix.

[0031] The expression of the sensitivity matrix of the node in the second scenario obtained by using the electrical signal of the input optimization simulation system based on the Jacobian matrix is: Where ΔP and ΔQ are respectively the active power change matrix and reactive power change matrix injected by the node in the second scenario, Δθ and ΔU are respectively the voltage phase angle and amplitude change matrices of the node, J is the Jacobian matrix, J -1 is the sensitivity matrix of the node in the second scenario.

[0032] In this embodiment, the second reactive resource is a photovoltaic inverter, and the second scenario is a sag mitigation scenario. In the formula, S PU With S QU are the voltage amplitude changes caused by the unit active and reactive power injected into the node in the second scenario, S Pθ With S Qθ are the voltage phase angle changes caused by the unit active and reactive power injected by the node in the second scenario. The expression for obtaining the second fitness score of the second reactive resource in the multi-modal reactive resource based on the sensitivity value is: Where S is the second fitness score of the second reactive resource, S i is the sensitivity value of the node in the second scenario, S min is the minimum sensitivity value of the node in the second scenario, S maxis the maximum value of the sensitivity value of the node in the second scenario. According to the above formula, the second fitness score of the second reactive resource can be obtained as (87.64, 91.46, 94.51, 92.16, 89.35). Through the sensitivity analysis characteristics of the Jacobian matrix, the accurate sensitivity value is obtained, and then the accurate sensitivity value is input into the corresponding calculation formula, which can accurately obtain the fitness score of the node in the second scenario, that is, the sag relief scenario, and then facilitate the performance of the voltage control scheme in the sag relief scenario through the node fitness score in the second scenario, which helps to improve the reliability and comprehensiveness of the scheme evaluation.

[0033] S4: A comprehensive evaluation system is constructed based on the analytic hierarchy process and the entropy weight method, and the weight of the first fitness score and the weight of the second fitness score are obtained based on the comprehensive evaluation system.

[0034] The S4 includes: S41: taking the first weight of the first fitness score and the first weight of the second fitness score as the parent indicator in the analytic hierarchy process in the comprehensive evaluation system, and defining the sub-indicators under the parent indicators in the analytic hierarchy process based on the evaluation requirements; S42: Compare the sub-indicators under the parent indicator in pairs, and then establish a judgment matrix, and obtain the first weight of the first fitness score and the first weight of the second fitness score based on the judgment matrix; S43: normalizing the sub-indicators based on the entropy weight method in the comprehensive evaluation system to obtain a normalized result, and obtaining a second weight of the first fitness score and a second weight of the second fitness score based on the normalized result; S44: Obtaining a weight of the first fitness score based on a first weight of the first fitness score and a second weight of the first fitness score, and obtaining a weight of the second fitness score based on the first weight of the second fitness score and the second weight of the second fitness score.

[0035] In S42, the judgment matrix A=(a ij ) n*m , where a ij It indicates the importance of the i-th sub-indicator under the parent indicator relative to the j-th sub-indicator, and n is the number of sub-indicators under the parent indicator.

[0036] In S42, the obtaining of the first weight of the first fitness score and the first weight of the second fitness score based on the judgment matrix includes: The judgment matrix is ​​summed up by columns to obtain the total number of elements in each column, and the judgment matrix is ​​normalized based on the total number of columns to obtain the process matrix; The process matrix is ​​summed row by row to obtain a weight vector, and a first weight of the first fitness score and a first weight of the second fitness score are obtained based on the weight vector.

[0037] In S43, the obtaining of the second weight of the first fitness score and the second weight of the second fitness score based on the normalization processing result includes: Based on the normalization result, the entropy value of the sub-indicator is calculated, the weight of the sub-indicator is obtained based on the entropy value, and the second weight of the first fitness score and the second weight of the second fitness score are obtained based on the weight of the sub-indicator.

[0038] In this embodiment, the sub-indicators are voltage level, load capacity, reliability, economy, and failure rate. The judgment matrix is ​​normalized based on the total number of columns, and the expression of the process matrix is ​​obtained as follows: In the formula, a ij It indicates the importance of the ith sub-indicator under the parent indicator relative to the jth sub-indicator, n is the number of sub-indicators under the parent indicator, b ij is the element in the i-th row and j-th column of the process matrix. The sub-indicators are divided into positive indicators and negative indicators. The positive indicators are voltage level, load capacity, and reliability, and the negative indicators are economy and failure rate. The positive indicators in the sub-indicators are normalized based on the entropy weight method in the comprehensive evaluation system, and the expression for obtaining the normalized processing result is: 1≤i≤m, 1≤j≤n, based on the entropy weight method in the comprehensive evaluation system, the negative indicators in the sub-indicators are normalized, and the expression for obtaining the normalized processing result is: 1≤i≤m,1≤j≤n,x ij is the value of the jth sub-index of the ith voltage regulation scheme, x j is the value of the jth sub-indicator. Based on the normalization processing results, the entropy value of the sub-indicator is calculated as follows: Based on the normalization processing results, the ratio of each sub-indicator under each scheme is calculated, and the expression is In the formula, 1≤i≤m, 1≤j≤n, m is the number of voltage regulation schemes, and n is the number of sub-indicators. The entropy value of the sub-indicator is calculated based on the ratio, and the expression is: In the formula, h j is the entropy value of the jth sub-indicator. The specific steps of obtaining the weight of the sub-indicator based on the entropy value are as follows: the information redundancy of each sub-indicator is calculated based on the entropy value, and the information redundancy d j =1-h j ; Calculate the weight of the sub-indicator based on information redundancy, the weight of the j-th sub-indicator By accurately obtaining the weights of the fitness scores of various reactive resources from multiple subjective and objective aspects, and further, linearly weighting the weights obtained from multiple subjective and objective aspects to obtain the combined weights of the fitness scores of reactive resources, the one-sidedness of single weighting is avoided, the rationality of weight distribution is improved, and further, to a certain extent, the reliability of the evaluation results is improved.

[0039] S5: Evaluate the voltage control scheme based on the first fitness score, the weight of the first fitness score, the second fitness score, and the weight of the second fitness score.

[0040] The S5 includes: S51: obtaining a first product of the first fitness score and the weight of the first fitness score, and obtaining a second product of the second fitness score and the weight of the second fitness score; S52: Evaluate the voltage control scheme based on the sum of the first product and the second product.

[0041] The scheme is evaluated by combining the fitness score of the reactive resource with the weight of the fitness score of the corresponding reactive resource, which significantly improves the comprehensiveness and reliability of the scheme evaluation.

[0042] In summary, different reactive resources have different adaptability in different scenarios, and the effects produced by reactive resources are also different. Figure 3-4 As shown in the figure, in the support scenario, after analyzing the voltage amplitude, OLTC and capacitors can make the voltage amplitude closer to the standard value. In the smoothing scenario, in the system where OLTC and SVC already exist, the impact of SVC on the system is relatively weak, but it still increases the voltage amplitude and is closer to the standard value. In the sag mitigation scenario, photovoltaic inverters can better reflect the sag mitigation function than other reactive devices, and the sensitivity value is larger, that is, the voltage is more affected by the addition of photovoltaic inverters. Therefore, by calculating the adaptability of different reactive resources in different scenarios to evaluate the voltage control scheme, the comprehensiveness and reliability of the scheme evaluation are significantly improved.

[0043] The specific implementation described above is a preferred implementation of the voltage control evaluation method based on the adaptability of multi-form reactive resources of the present invention, and is not intended to limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to this specific implementation. All equivalent changes made in accordance with the shape and structure of the present invention are within the protection scope of the present invention.

Claims

1. A voltage control evaluation method based on adaptability of multi-form reactive resources, characterized in that: The following steps are involved: S1: Based on the operating characteristics of multi-form reactive resources and the reactive resource demand of the distribution network in different scenarios, the voltage control scheme is obtained, and the simulated power system is improved based on the voltage control scheme to obtain an optimized simulation system; S2: Based on power flow calculation, obtain the electrical parameters of the nodes in the optimization simulation system in the first scenario in different scenarios, and obtain the first fitness score of the first reactive resource in the multi-form reactive resources based on the electrical parameters; S3: Based on the Jacobian matrix, using the electrical signal of the input optimization simulation system to obtain a sensitivity value of the node in a second scenario in different scenarios, and obtaining a second fitness score of a second reactive resource in the multi-modal reactive resource based on the sensitivity value; S4: construct a comprehensive evaluation system based on the analytic hierarchy process and the entropy weight method, and obtain the weight of the first fitness score and the weight of the second fitness score based on the comprehensive evaluation system; S5: Evaluate the voltage control scheme based on the first fitness score, the weight of the first fitness score, the second fitness score, and the weight of the second fitness score.

2. The voltage regulation and evaluation method based on adaptability of multi-form reactive resources according to claim 1 is characterized in that: In S2, the expression for obtaining the electrical parameters of the nodes in the optimization simulation system in the first scenario in different scenarios based on the power flow calculation is: In the formula, represents the active power injected by node i in the nodes under the first scenario, represents the reactive power injected by node i in the first scenario, U i is the voltage phase difference at node i, U j is the voltage amplitude of node j in the node, θ ij is the voltage phase difference between node i and node j, G ij and B ij are the conductance and susceptance between node i and node j in the admittance matrix, Ω N is the set of all nodes except the PQ node, Ω PQ is the set of PQ nodes in the node, N bus Indicates the total number of nodes.

3. The voltage regulation and evaluation method based on adaptability of multi-form reactive resources according to claim 1 is characterized in that: In S2, obtaining a first fitness score of a first reactive resource in the multi-form reactive resources based on the electrical parameter includes: Obtaining a fitness score of the node in the supporting scenario based on the electrical parameters of the node in the supporting scenario in the first scenario and the reference electrical parameters; Obtaining fitness scores of nodes in the stabilization scenario based on electrical parameters of nodes in the simulated power system in the stabilization scenario in the first scenario and electrical parameters of nodes in the optimized simulation system in the stabilization scenario in the first scenario; The fitness score of the node in the supporting scenario and the fitness score of the node in the stabilizing scenario are the first fitness score of the first reactive resource.

4. The voltage regulation and evaluation method based on adaptability of multi-form reactive resources according to claim 1 is characterized in that: In S3, the step of obtaining the sensitivity value of the node in the second scenario in different scenarios by using the electrical signal of the input optimization simulation system based on the Jacobian matrix includes: Based on the Jacobian matrix, the sensitivity matrix of the node in the second scenario is obtained by using the electrical signal of the input optimization simulation system; and the sensitivity value of the node in the second scenario is obtained based on the sensitivity matrix.

5. The voltage regulation and evaluation method based on adaptability of multi-form reactive resources according to claim 4 is characterized in that: The expression of the sensitivity matrix of the node in the second scenario obtained by using the electrical signal of the input optimization simulation system based on the Jacobian matrix is: Where ΔP and ΔQ are respectively the active power change matrix and reactive power change matrix injected by the node in the second scenario, Δθ and ΔU are respectively the voltage phase angle and amplitude change matrices of the node, J is the Jacobian matrix, J -1 is the sensitivity matrix of the node in the second scenario.

6. The voltage regulation and evaluation method based on adaptability of multi-form reactive resources according to claim 1 is characterized in that: The S4 includes: S41: taking the first weight of the first fitness score and the first weight of the second fitness score as the parent indicator in the analytic hierarchy process in the comprehensive evaluation system, and defining the sub-indicators under the parent indicators in the analytic hierarchy process based on the evaluation requirements; S42: Compare the sub-indicators under the parent indicator in pairs, and then establish a judgment matrix, and obtain the first weight of the first fitness score and the first weight of the second fitness score based on the judgment matrix; S43: normalizing the sub-indicators based on the entropy weight method in the comprehensive evaluation system to obtain a normalized result, and obtaining a second weight of the first fitness score and a second weight of the second fitness score based on the normalized result; S44: Obtaining a weight of the first fitness score based on a first weight of the first fitness score and a second weight of the first fitness score, and obtaining a weight of the second fitness score based on the first weight of the second fitness score and the second weight of the second fitness score.

7. The voltage regulation and evaluation method based on adaptability of multi-form reactive resources according to claim 6 is characterized in that: In S42, the judgment matrix A=(a ij ) n*n , where a ij It indicates the importance of the ith sub-indicator under the parent indicator relative to the ith sub-indicator, and n is the number of sub-indicators under the parent indicator.

8. The voltage regulation and evaluation method based on adaptability of multi-form reactive resources according to claim 6 is characterized in that: In S42, the step of obtaining the first weight of the first fitness score and the first weight of the second fitness score based on the judgment matrix includes: summing the judgment matrix by columns to obtain the total number of elements in each column, normalizing the judgment matrix based on the total number of columns, and thereby obtaining the process matrix; The process matrix is ​​summed row by row to obtain a weight vector, and a first weight of the first fitness score and a first weight of the second fitness score are obtained based on the weight vector.

9. The voltage regulation and evaluation method based on adaptability of multi-form reactive resources according to claim 6 is characterized in that: In S43, the obtaining of the second weight of the first fitness score and the second weight of the second fitness score based on the normalization processing result includes: Based on the normalization result, the entropy value of the sub-indicator is calculated, the weight of the sub-indicator is obtained based on the entropy value, and the second weight of the first fitness score and the second weight of the second fitness score are obtained based on the weight of the sub-indicator.

10. The voltage regulation and evaluation method based on adaptability of multi-form reactive resources according to claim 1 is characterized in that: The S5 includes: S51: obtaining a first product of the first fitness score and the weight of the first fitness score, and obtaining a second product of the second fitness score and the weight of the second fitness score; S52: Evaluate the voltage control scheme based on the sum of the first product and the second product.

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